Select n elements in matrix left-wise based on certain value - arrays

I have a logical matrix A, and I would like to select all the elements to the left of each of my 1s values given a fixed distant. Let's say my distance is 4, I would like to (for instance) replace with a fixed value (saying 2) all the 4 cells at the left of each 1 in A.
A= [0 0 0 0 0 1 0
0 1 0 0 0 0 0
0 0 0 0 0 0 0
0 0 0 0 1 0 1]
B= [0 2 2 2 2 1 0
2 1 0 0 0 0 0
0 0 0 0 0 0 0
2 2 2 2 2 2 1]
In B is what I would like to have, considering also overwrting (last row in B), and cases where there is only 1 value at the left of my 1 and not 4 as the fixed searching distance (second row).

How about this lovely one-liner?
n = 3;
const = 5;
A = [0 0 0 0 0 1 0;
0 1 0 0 0 0 0;
0 0 0 0 0 0 0;
0 0 0 0 1 0 1]
A(bsxfun(#ne,fliplr(filter(ones(1,1+n),1,fliplr(A),[],2)),A)) = const
results in:
A =
0 0 5 5 5 1 0
5 1 0 0 0 0 0
0 0 0 0 0 0 0
0 5 5 5 5 5 1
here some explanations:
Am = fliplr(A); %// mirrored input required
Bm = filter(ones(1,1+n),1,Am,[],2); %// moving average filter for 2nd dimension
B = fliplr(Bm); %// back mirrored
mask = bsxfun(#ne,B,A) %// mask for constants
A(mask) = const

Here is a simple solution you could have come up with:
w=4; % Window size
v=2; % Desired value
B = A;
for r=1:size(A,1) % Go over all rows
for c=2:size(A,2) % Go over all columns
if A(r,c)==1 % If we encounter a 1
B(r,max(1,c-w):c-1)=v; % Set the four spots before this point to your value (if possible)
end
end
end

d = 4; %// distance
v = 2; %// value
A = fliplr(A).'; %'// flip matrix, and transpose to work along rows.
ind = logical( cumsum(A) ...
- [ zeros(size(A,1)-d+2,size(A,2)); cumsum(A(1:end-d-1,:)) ] - A );
A(ind) = v;
A = fliplr(A.');
Result:
A =
0 2 2 2 2 1 0
2 1 0 0 0 0 0
0 0 0 0 0 0 0
2 2 2 2 2 2 1

Approach #1 One-liner using imdilate available with Image Processing Toolbox -
A(imdilate(A,[ones(1,4) zeros(1,4+1)])==1)=2
Explanation
Step #1: Create a morphological structuring element to be used with imdilate -
morph_strel = [ones(1,4) zeros(1,4+1)]
This basically represents a window extending n places to the left with ones and n places to the right including the origin with zeros.
Step #2: Use imdilate that will modify A such that we would have 1 at all four places to the left of each 1 in A -
imdilate_result = imdilate(A,morph_strel)
Step #3: Select all four indices for each 1 of A and set them to 2 -
A(imdilate_result==1)=2
Thus, one can write a general form for this approach as -
A(imdilate(A,[ones(1,window_length) zeros(1,window_length+1)])==1)=new_value
where window_length would be 4 and new_value would be 2 for the given data.
Approach #2 Using bsxfun-
%// Paramters
window_length = 4;
new_value = 2;
B = A' %//'
[r,c] = find(B)
extents = bsxfun(#plus,r,-window_length:-1)
valid_ind1 = extents>0
jump_factor = (c-1)*size(B,1)
extents_valid = extents.*valid_ind1
B(nonzeros(bsxfun(#plus,extents_valid,jump_factor).*valid_ind1))=new_value
B = B' %// B is the desired output

Related

MATLAB : Obtain a matrix by adding its last lines to the first lines of the basic matrix

I have a matrix B and I would like to obtain a new matrix C from B by adding its last w*a rows to the first w*a rows (w and a will be defined afterwards).
My matrix B is generally defined by :
I would like to obtain matrix C defined in a general way by:
The characteristics of matrices B and C are:
L and w are defined real values;
B0,B1,...,Bw are of dimension: a by b;
B is of dimension: [(L+w)×a] by (L×b);
C is of dimension: (L×a) by (L×b).
Example: For L = 4 and w = 2 I obtain the following matrix B:
The w*a = 2*1 = 2 last rows of B are:
The w*a = 2*1 = 2 first rows of B are:
By adding the two matrices we have:
The matrix C thus obtained is then:
For B0 = [1 0], B1 = [0 1] and B2 = [1 1]. We obtain :
B0, B1 and B2 are of dimension a by b i.e. 1 by 2;
B is of dimension: [(L+w )×(a)] by (L×b) i.e. [(4+2)×1] by (4×2) i.e. 6 by 8;
C is of dimension: (L×a) by (L×b) i.e. (4×1) by (4×2) i.e. 4 by 8.
The matrices B and C that I get are as follows:
B =
1 0 0 0 0 0 0 0
0 1 1 0 0 0 0 0
1 1 0 1 1 0 0 0
0 0 1 1 0 1 1 0
0 0 0 0 1 1 0 1
0 0 0 0 0 0 1 1
C =
1 0 0 0 1 1 0 1
0 1 1 0 0 0 1 1
1 1 0 1 1 0 0 0
0 0 1 1 0 1 1 0
I would like to have some suggestions on how to program this construction so that from a given matrix B I can deduce the matrix C.
Matlab's range indexing should help you do this in a few steps. The key things to remember are that ranges are inclusive, i.e. A[1:3] is a three 3x1 matrix, and that you can use the keyword end to automatically index the end of the matrix row or column.
%% Variables from OP example
w = 2;
L = 4;
B0 = [1 0];
B1 = [0 1];
B2 = [1 1];
[a, b] = size(B0);
% Construct B
BX = [B0;B1;B2]
B = zeros((L+w)*a, L*b);
for ii = 0:L-1
B(ii+1:ii+w+1, ii*b+1:ii*b+b) = BX;
end
%% Construct C <- THIS PART IS THE ANSWER TO THE QUESTION
% Grab first rows of B
B_first = B(1:end-w*a, :) % Indexing starts at first row, continues to w*a rows before the end, and gets all columns
% Grab last rows of B
B_last = B(end-w*a+1:end, :); % Indexing starts at w*a rows before the end, continues to end. Plus one is needed to avoid off by one error.
% Initialize C to be the same as B_first
C = B_first;
% Add B_last to the first rows of C
C(1:w*a, :) = C(1:w*a, :) + B_last;
I get the output
C =
1 0 0 0 0 0 1 1 0 1
0 1 1 0 0 0 0 0 1 1
1 1 0 1 1 0 0 0 0 0
0 0 1 1 0 1 1 0 0 0
0 0 0 0 1 1 0 1 1 0

How to balance unique values in an array Matlab

I have a vector
Y = [1 1 0 0 0 1 1 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 1 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0]
1 occurs 17 times
0 occurs 21 times
How can I randomly remove 0s so that both values have equal amounts, such as 1 (17 times) and 0 (17 times)?
This should also work on much bigger matrix.
Starting with your example
Y = [1 1 0 0 0 1 1 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 1 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0]
You can do the following:
% Get the indices of the value which is more common (`0` here)
zeroIdx = find(~Y); % equivalent to find(Y==0)
% Get random indices to remove
remIdx = randperm(nnz(~Y), nnz(~Y) - nnz(Y));
% Remove elements
Y(zeroIdx(remIdx)) = [];
You could combine the last two lines, but I think it would be less clear.
The randperm line is choosing the correct number of elements to remove from random indices between 1 and the number of zeros.
If the data can only have two values
Values are assumed to be 0 and 1. The most common value is randomly removed to equalize their counts:
Y = [1 1 0 0 0 1 1 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 1 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0]; % data
ind0 = find(Y==0); % indices of zeros
ind1 = find(Y==1); % indices of ones
t(1,1:numel(ind0)) = ind0(randperm(numel(ind0))); % random permutation of indices of zeros
t(2,1:numel(ind1)) = ind1(randperm(numel(ind1))); % same for ones. Pads shorter row with 0
t = t(:, all(t,1)); % keep only columns that don't have padding
result = Y(sort(t(:))); % linearize, sort and use those indices into the data
Generalization for more than two values
Values are arbitrary. All values except the least common one are randomly removed to equalize their counts:
Y = [0 1 2 0 2 1 1 2 0 2 1 2 2 0 0]; % data
vals = [0 1 2]; % or use vals = unique(Y), but absent values will not be detected
t = [];
for k = 1:numel(vals) % loop over values
ind_k = find(Y==vals(k));
t(k, 1:numel(ind_k)) = ind_k(randperm(numel(ind_k)));
end
t = t(:, all(t,1));
result = Y(sort(t(:)));

How to change elements of a matrix with reference to a vector of column indices without using for-loop?

I have a matrix
a =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
and b vector
b =
1 2 3 4 5 5
I want to replace value of each row in a matrix with reference value of b matrix value and finally generate a matrix as follows without using for loop.
a_new =
1 0 0 0 0
0 1 0 0 0
0 0 1 0 0
0 0 0 1 0
0 0 0 0 1
0 0 0 0 1
if first element of b, b(1) = 1 so change take first row of a vector and make first element as 1 because b(1) = 1.
How can I implement this without using for loop?
Sure. You only need to build a linear index from b and use it to fill the values in a:
a = zeros(6,5); % original matrix
b = [1 2 3 4 5 5]; % row or column vector with column indices into a
ind = (1:size(a,1)) + (b(:).'-1)*size(a,1); % build linear index
a(ind) = 1; % fill value at those positions
Same as Luis Mendo's answer, but using the dedicated function sub2ind:
a( sub2ind(size(a),(1:numel(b)).',b(:)) ) = 1
Also via the subscript to indices conversion way,
a = zeros(6,5);
b = [1 2 3 4 5 5];
idx = sub2ind(size(a), [1:6], b); % 1:6 just to create the row index per b entry
a(idx) = 1
any of these methods works in Octave:
bsxfun(#eq, [1:5 5]',(1:5))
[1:5 5].' == (1:5)

Create a "pyramid" matrix

Say I'm given a symmetric row vector with an odd length where each element is smaller than the next one in the first half of the vector and each element is bigger than the next one in the second half and the middle element is the biggest. (e.g [1 2 3 2 1] or [10 20 50 20 10]).
I want to create a square matrix where this row vector is its middle row and the equivalent column vector (v') is its middle column and each other row or column is a reduced version of the given vector according to the middle element in this row or column. And when there are no more "original elements" we put 0.
Examples:
if v = [1 2 3 2 1] we get
0 0 1 0 0
0 1 2 1 0
1 2 3 2 1
0 1 2 1 0
0 0 1 0 0
if v = [3 5 3] we get
0 3 0
3 5 3
0 3 0
What I did so far: I managed to create a matrix with v as the middle row and v' as the middle column with this code I wrote:
s = length(vector);
matrix= zeros(s);
matrix(round(s/2),:) = vector;
matrix(:, round(s/2)) = vector';
but got stuck with assigning the other values.
A more hands-on approach is to produce your matrix as a mosaic, starting from a hankel matrix. For performance comparison, here's a version using the same format as #Divakar's solution:
function out=pyramid_hankel(v)
%I suggest checking v here
%it should be odd in length and a palindrome
i0=ceil(length(v)/2);
v2=v(i0:end);
Mtmp=hankel(v2);
out=zeros(length(v));
out(i0:end,i0:end)=Mtmp;
out(1:i0-1,i0:end)=flipud(Mtmp(2:end,:));
out(:,1:i0-1)=fliplr(out(:,i0+1:end));
>> pyramid_hankel([1 2 3 2 1])
ans =
0 0 1 0 0
0 1 2 1 0
1 2 3 2 1
0 1 2 1 0
0 0 1 0 0
For v=[1 2 3 2 1] the starting block is hankel([3 2 1]), which is
ans =
3 2 1
2 1 0
1 0 0
From here it should be clear what's happening.
Here's one approach -
function out = pyramid(v)
hlen = (numel(v)+1)/2;
updown_vec = [1:(numel(v)+1)/2 (numel(v)-1)/2:-1:1];
upper_part = cumsum(bsxfun(#le,(hlen:-1:1)',updown_vec)); %//'
out = [upper_part ; flipud(upper_part(1:end-1,:))];
out = changem(out,v,updown_vec);
Here's another approach, sort of simpler maybe -
function out = pyramid_v2(v)
hlen = (numel(v)+1)/2;
updown_vec = [1:(numel(v)+1)/2 (numel(v)-1)/2:-1:1];
mask = bsxfun(#le,([hlen:-1:1 2:hlen])',updown_vec); %//'
M = double(mask);
M(hlen+1:end,:) = -1;
out = changem(cumsum(M).*mask,v,updown_vec);
Sample runs -
>> v = [1 2 3 2 1];
>> pyramid(v)
ans =
0 0 1 0 0
0 1 2 1 0
1 2 3 2 1
0 1 2 1 0
0 0 1 0 0
>> v = [3 5 3];
>> pyramid(v)
ans =
0 3 0
3 5 3
0 3 0
>> v = [99,3,78,55,78,3,99];
>> pyramid(v)
ans =
0 0 0 99 0 0 0
0 0 99 3 99 0 0
0 99 3 78 3 99 0
99 3 78 55 78 3 99
0 99 3 78 3 99 0
0 0 99 3 99 0 0
0 0 0 99 0 0 0
Here's another approach:
v = [1 2 3 2 1]; %// symmetric, odd size
m = (numel(v)-1)/2;
w = [0 v(1:m+1)];
t = abs(-m:m);
result = w(max(m+2-bsxfun(#plus, t, t.'),1));

A question about matrix manipulation

Given a 1*N matrix or an array, how do I find the first 4 elements which have the same value and then store the index for those elements?
PS:
I'm just curious. What if we want to find the first 4 elements whose value differences are within a certain range, say below 2? For example, M=[10,15,14.5,9,15.1,8.5,15.5,9.5], the elements I'm looking for will be 15,14.5,15.1,15.5 and the indices will be 2,3,5,7.
If you want the first value present 4 times in the array 'tab' in Matlab, you can use
num_min = 4
val=NaN;
for i = tab
if sum(tab==i) >= num_min
val = i;
break
end
end
ind = find(tab==val, num_min);
By instance with
tab = [2 4 4 5 4 6 4 5 5 4 6 9 5 5]
you get
val =
4
ind =
2 3 5 7
Here is my MATLAB solution:
array = randi(5, [1 10]); %# random array of integers
n = unique(array)'; %'# unique elements
[r,~] = find(cumsum(bsxfun(#eq,array,n),2) == 4, 1, 'first');
if isempty(r)
val = []; ind = []; %# no answer
else
val = n(r); %# the value found
ind = find(array == val, 4); %# indices of elements corresponding to val
end
Example:
array =
1 5 3 3 1 5 4 2 3 3
val =
3
ind =
3 4 9 10
Explanation:
First of all, we extract the list of unique elements. In the example used above, we have:
n =
1
2
3
4
5
Then using the BSXFUN function, we compare each unique value against the entire vector array we have. This is equivalent to the following:
result = zeros(length(n),length(array));
for i=1:length(n)
result(i,:) = (array == n(i)); %# row-by-row
end
Continuing with the same example we get:
result =
1 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 1 0 0
0 0 1 1 0 0 0 0 1 1
0 0 0 0 0 0 1 0 0 0
0 1 0 0 0 1 0 0 0 0
Next we call CUMSUM on the result matrix to compute the cumulative sum along the rows. Each row will give us how many times the element in question appeared so far:
>> cumsum(result,2)
ans =
1 1 1 1 2 2 2 2 2 2
0 0 0 0 0 0 0 1 1 1
0 0 1 2 2 2 2 2 3 4
0 0 0 0 0 0 1 1 1 1
0 1 1 1 1 2 2 2 2 2
Then we compare that against four cumsum(result,2)==4 (since we want the location where an element appeared for the forth time):
>> cumsum(result,2)==4
ans =
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 1
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
Finally we call FIND to look for the first appearing 1 according to a column-wise order: if we traverse the matrix from the previous step column-by-column, then the row of the first appearing 1 indicates the index of the element we are looking for. In this case, it was the third row (r=3), thus the third element in the unique vector is the answer val = n(r). Note that if we had multiple elements repeated 4 times or more in the original array, then the one first appearing for the forth time will show up first as a 1 going column-by-column in the above expression.
Finding the indices of the corresponding answer value is a simple call to FIND...
Here is C++ code
std::map<int,std::vector<int> > dict;
std::vector<int> ans(4);//here we will store indexes
bool noanswer=true;
//my_vector is a vector, which we must analize
for(int i=0;i<my_vector.size();++i)
{
std::vector<int> &temp = dict[my_vector[i]];
temp.push_back(i);
if(temp.size()==4)//we find ans
{
std::copy(temp.begin(),temp.end(),ans.begin() );
noanswer = false;
break;
}
}
if(noanswer)
std::cout<<"No Answer!"<<std::endl;
Ignore this and use Amro's mighty solution . . .
Here is how I'd do it in Matlab. The matrix can be any size and contain any range of values and this should work. This solution will automatically find a value and then the indicies of the first 4 elements without being fed the search value a priori.
tab = [2 5 4 5 4 6 4 5 5 4 6 9 5 5]
%this is a loop to find the indicies of groups of 4 identical elements
tot = zeros(size(tab));
for nn = 1:numel(tab)
idxs=find(tab == tab(nn), 4, 'first');
if numel(idxs)<4
tot(nn) = Inf;
else
tot(nn) = sum(idxs);
end
end
%find the first 4 identical
bestTot = find(tot == min(tot), 1, 'first' );
%store the indicies you are interested in.
indiciesOfInterst = find(tab == tab(bestTot), 4, 'first')
Since I couldn't easily understand some of the solutions, I made that one:
l = 10; m = 5; array = randi(m, [1 l])
A = zeros(l,m); % m is the maximum value (may) in array
A(sub2ind([l,m],1:l,array)) = 1;
s = sum(A,1);
b = find(s(array) == 4,1);
% now in b is the index of the first element
if (~isempty(b))
find(array == array(b))
else
disp('nothing found');
end
I find this easier to visualize. It fills '1' in all places of a square matrix, where values in array exist - according to their position (row) and value (column). This is than summed up easily and mapped to the original array. Drawback: if array contains very large values, A may get relative large too.
You're PS question is more complicated. I didn't have time to check each case but the idea is here :
M=[10,15,14.5,9,15.1,8.5,15.5,9.5]
val = NaN;
num_min = 4;
delta = 2;
[Ms, iMs] = sort(M);
dMs = diff(Ms);
ind_min=Inf;
n = 0;
for i = 1:length(dMs)
if dMs(i) <= delta
n=n+1;
else
n=0;
end
if n == (num_min-1)
if (iMs(i) < ind_min)
ind_min = iMs(i);
end
end
end
ind = sort(iMs(ind_min + (0:num_min-1)))
val = M(ind)

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